An adaptive control system and method for carbon dioxide monitoring management

Abstract

The application relates to the technical field of carbon dioxide monitoring adaptive control, and discloses an adaptive control system and method for carbon dioxide monitoring management, which comprises the following steps: collecting data according to a preset flow detection point position; identifying the carbon dioxide state in a carbon dioxide monitoring process according to the collected data to obtain a carbon dioxide real-time state; and analyzing the carbon dioxide flow according to the carbon dioxide real-time state and the collected data, adjusting the carbon dioxide monitoring management mode, and obtaining carbon dioxide real-time flow. The application corrects the flow monitoring result based on the real-time state of carbon dioxide, obtains more accurate carbon dioxide real-time flow, improves the accuracy of flow monitoring, realizes real-time monitoring adaptive control of carbon dioxide flow, provides reliable data support for operators, so as to timely adjust oil displacement parameters, and guarantee efficient and stable operation of the oil displacement process.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of carbon dioxide monitoring adaptive control, and particularly relates to an adaptive control system and method for carbon dioxide monitoring management. BACKGROUND

[0002] At present, in the process of carbon dioxide displacement of crude oil, the carbon dioxide flow cannot be monitored when the carbon dioxide is miscible with the crude oil. If the carbon dioxide flow is too high, the formation pressure is too high and the cost is increased. If the carbon dioxide flow is too low, the oil displacement effect is poor, which affects the oil production efficiency. Obviously, the abnormal carbon dioxide flow will affect the oil quality and oil production efficiency. At present, there is no method for accurately and adaptively controlling the carbon dioxide in the monitoring process, and therefore there are many deficiencies. SUMMARY

[0003] In view of the deficiencies of the prior art, the main purpose of the present application is to provide an adaptive control system and method for carbon dioxide monitoring management, which can effectively solve the problems in the background art. The specific technical scheme of the present application is as follows:

[0004] An adaptive control method for carbon dioxide monitoring management, comprising:

[0005] According to the preset flow detection point position, the acquisition data of a plurality of sensors is obtained;

[0006] According to the acquisition data, the state of carbon dioxide in the carbon dioxide monitoring process is identified to obtain the real-time state of carbon dioxide;

[0007] According to the real-time state of carbon dioxide and the acquisition data, the carbon dioxide flow is analyzed, the carbon dioxide monitoring management mode is adjusted, the real-time flow of carbon dioxide is obtained, and the carbon dioxide flow monitoring process is adaptively controlled.

[0008] Specifically, the acquisition data of a plurality of sensors is obtained according to the preset flow detection point position, comprising:

[0009] Flow sensors, temperature sensors and pressure sensors are arranged at the injection inlet, branch point and outlet of the carbon dioxide injection pipeline and between different levels of the oil reservoir, and the acquisition data of each sensor is obtained at a preset time interval.

[0010] Specifically, the state of carbon dioxide in the carbon dioxide monitoring process is identified according to the acquisition data to obtain the real-time state of carbon dioxide, comprising:

[0011] According to the temperature data and pressure data in the acquisition data, the carbon dioxide state characteristics are calculated;

[0012] Input the carbon dioxide state feature into a preset phase state recognition model to recognize the carbon dioxide state in the carbon dioxide monitoring process to obtain the carbon dioxide state, wherein the carbon dioxide state includes a gaseous state, a liquid state, a gas-liquid mixed phase state and a supercritical mixed phase state;

[0013] According to the carbon dioxide state, a carbon dioxide state curve is drawn to obtain the real-time state of the carbon dioxide.

[0014] Specifically, the carbon dioxide state feature is calculated according to the temperature data and the pressure data in the collected data, including:

[0015] According to the temperature data and the pressure data in the collected data, the corresponding carbon dioxide state parameters are calculated by using a preset carbon dioxide phase state equation;

[0016] The carbon dioxide state parameters are subjected to feature extraction to obtain state features related to the carbon dioxide state.

[0017] Specifically, the carbon dioxide real-time state is combined with the collected data to analyze the carbon dioxide flow, adjust the carbon dioxide monitoring management mode, and obtain the carbon dioxide real-time flow, including:

[0018] For gaseous carbon dioxide and liquid carbon dioxide, the initial flow monitoring value is corrected by a corresponding state correction matrix to obtain a gaseous carbon dioxide corrected flow and a liquid carbon dioxide corrected flow;

[0019] For gas-liquid mixed phase state carbon dioxide, the flow monitoring value is corrected according to the phase content of the gas phase and the liquid phase in the gas-liquid mixed phase state to obtain a gas-liquid mixed phase state carbon dioxide corrected flow;

[0020] For supercritical mixed phase state carbon dioxide, the flow monitoring value is corrected according to the flow characteristics of the supercritical mixed phase state carbon dioxide to obtain a supercritical mixed phase state carbon dioxide corrected flow;

[0021] According to the carbon dioxide real-time state, the gaseous carbon dioxide corrected flow, the liquid carbon dioxide corrected flow, the gas-liquid mixed phase state carbon dioxide corrected flow and the supercritical mixed phase state carbon dioxide corrected flow are combined to obtain the carbon dioxide real-time flow.

[0022] Specifically, for gaseous carbon dioxide and liquid carbon dioxide, the initial flow monitoring value is corrected by a corresponding state correction matrix to obtain a gaseous carbon dioxide corrected flow and a liquid carbon dioxide corrected flow, including:

[0023] According to the temperature and pressure of gaseous carbon dioxide and liquid carbon dioxide respectively, a gaseous flow correction coefficient and a liquid flow correction coefficient are obtained by a spline interpolation method;

[0024] According to the state of gaseous carbon dioxide and liquid carbon dioxide, a gaseous state correction matrix and a liquid state correction matrix are respectively constructed;

[0025] According to the gaseous flow correction coefficient and the gaseous state correction matrix, an initial gaseous flow monitoring value is corrected to obtain a gaseous carbon dioxide correction flow;

[0026] According to the liquid flow correction coefficient and the liquid state correction matrix, an initial liquid flow monitoring value is corrected to obtain a liquid carbon dioxide correction flow.

[0027] Specifically, for the gaseous-liquid mixed phase state carbon dioxide, according to the phase content of the gas phase and the liquid phase in the gaseous-liquid mixed phase state, a flow monitoring value is corrected to obtain a gaseous-liquid mixed phase state carbon dioxide correction flow, which includes:

[0028] According to the state of the gaseous-liquid mixed phase state carbon dioxide, the phase content of the gas phase and the liquid phase in the gaseous-liquid mixed phase state is obtained;

[0029] Through a polynomial interpolation method, the flow correction coefficients of the gas phase and the liquid phase are calculated to obtain a gas phase flow correction coefficient and a liquid phase flow correction coefficient;

[0030] According to the interaction of the gas-liquid two phases in the flow process, a gaseous-liquid mixed phase state correction matrix is constructed;

[0031] According to the phase content, an initial gaseous-liquid mixed phase flow monitoring value is distributed to the gas phase and the liquid phase to obtain an initial gas phase flow and an initial liquid phase flow;

[0032] The initial gas phase flow and the initial liquid phase flow are respectively calculated with the corresponding gas phase flow correction coefficient and the liquid phase flow correction coefficient to obtain a corrected gas phase flow and a corrected liquid phase flow;

[0033] According to the corrected gas phase flow and the corrected liquid phase flow and the gaseous-liquid mixed phase state correction matrix, a gaseous-liquid mixed phase state carbon dioxide correction flow is calculated.

[0034] Specifically, for the supercritical mixed phase state carbon dioxide, according to the flow characteristics of the supercritical mixed phase state carbon dioxide, a flow monitoring value is corrected to obtain a supercritical mixed phase state carbon dioxide correction flow, which includes:

[0035] According to the relationship between the supercritical mixed phase state carbon dioxide flow and the pressure and the temperature, a supercritical state flow correction coefficient is calculated;

[0036] According to the flow characteristics of the supercritical mixed phase state carbon dioxide, a supercritical state correction matrix is constructed;

[0037] According to the supercritical state flow correction coefficient, the initial supercritical state flow monitoring value is corrected to obtain a supercritical mixed-phase state carbon dioxide correction flow.

[0038] Specifically, the supercritical state flow correction coefficient is calculated according to the relationship between the supercritical mixed-phase state carbon dioxide flow and the pressure and temperature, and the supercritical state flow correction coefficient is calculated according to the relationship between the supercritical mixed-phase state carbon dioxide flow and the pressure and temperature.

[0039] According to the relationship between the supercritical mixed-phase state carbon dioxide flow and the pressure and temperature, an interpolation model is constructed by combining a Gaussian function, wherein the function parameters of the Gaussian function are determined by an optimal value through a cross-validation method.

[0040] According to the preset interpolation point and the interpolation model, the supercritical state flow correction coefficient is calculated.

[0041] An adaptive control system for carbon dioxide monitoring and management is used to implement the adaptive control method for carbon dioxide monitoring and management, and comprises:

[0042] A data acquisition module acquires acquisition data of multiple sensors according to a preset flow detection point position.

[0043] A carbon dioxide state recognition module recognizes the carbon dioxide state in the carbon dioxide monitoring process according to the acquisition data to obtain a carbon dioxide real-time state.

[0044] A carbon dioxide flow monitoring module analyzes the carbon dioxide flow according to the carbon dioxide real-time state and the acquisition data, adjusts the carbon dioxide monitoring and management mode, and obtains a carbon dioxide real-time flow to adaptively control the carbon dioxide flow monitoring process.

[0045] Compared with the prior art, the present application has the following beneficial effects:

[0046] The present application identifies the real-time state of carbon dioxide based on the sensor acquisition data at multiple positions of a carbon dioxide oil displacement system, corrects the flow monitoring result, accurately judges the real-time state of carbon dioxide, corrects the initial flow detection result according to the carbon dioxide state, obtains a more accurate carbon dioxide real-time flow, improves the accuracy of flow monitoring, realizes real-time monitoring of the carbon dioxide flow in the oil displacement process, provides reliable data support for the operating personnel, adjusts the oil displacement parameters in time, guarantees the efficient and stable operation of the oil displacement process, and realizes real-time management and control of the carbon dioxide monitoring process. BRIEF DESCRIPTION OF DRAWINGS

[0047] Figure 1 The workflow of the adaptive control method for carbon dioxide monitoring and management in embodiment 1 of the present application is described.

[0048] Figure 2 A schematic diagram for the flow detection point in embodiment 1 of the present application;

[0049] Figure 3 A workflow diagram for real-time carbon dioxide flow analysis in embodiment 1 of the present application;

[0050] Figure 4 A structural schematic diagram of an adaptive control system for carbon dioxide monitoring management in embodiment 2 of the present application. DETAILED DESCRIPTION

[0051] In order to make the above objectives, features and advantages of the present application more apparent and comprehensible, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0052] In the following description, many specific details are set forth in order to provide a thorough understanding of the present application. However, the present application can be practiced without the specific details, other than in the examples, set forth in the following description, and it will be apparent to those skilled in the art that the present application can be practiced with other than the specific details set forth in the following description.

[0053] Secondly, the "one embodiment" or "embodiment" referred to herein means that the specific features, structures or characteristics can be included in at least one implementation of the present application. The "in one embodiment" appearing in different places in the specification does not mean the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments.

[0054] Embodiment 1

[0055] The present embodiment provides an adaptive control method for carbon dioxide monitoring management, as shown in Figure 1 , the adaptive control method for carbon dioxide monitoring management comprises:

[0056] S101, acquiring the collection data of a plurality of sensors according to the preset flow detection point position;

[0057] S102, identifying the carbon dioxide state in the carbon dioxide monitoring process according to the collection data, to obtain the real-time state of carbon dioxide;

[0058] S103, combining the real-time state of carbon dioxide with the collection data to analyze the carbon dioxide flow, adjusting the carbon dioxide monitoring management mode, obtaining the real-time flow of carbon dioxide, to adaptively control the carbon dioxide flow monitoring process.

[0059] Currently, when carbon dioxide is miscible, carbon dioxide and crude oil can be in a supercritical state and a gas-liquid miscible state. The supercritical state refers to a state where a substance is higher than its critical temperature and critical pressure. For the carbon dioxide and crude oil system, when the temperature and pressure of carbon dioxide are higher than its critical temperature and critical pressure, respectively, carbon dioxide will be in a supercritical state. The gas-liquid miscible state refers to a state where, under certain temperature and pressure conditions, carbon dioxide and crude oil system have both gas and liquid phases, and the two are in a dynamic equilibrium miscible state. In these two states, carbon dioxide is dissolved in crude oil, which will affect the oil displacement process. In this embodiment, the flow of carbon dioxide is monitored based on the different states of carbon dioxide, and the influence of different phases of carbon dioxide on the flow acquisition results is reduced.

[0060] In this embodiment, carbon dioxide is used for oil displacement in the process of collecting underground crude oil. Different flow and state information of carbon dioxide can be collected at different positions, and multiple sensors are set at the preset flow detection points to collect data. For example, flow sensors are set at different positions of the pipeline to measure the flow of carbon dioxide; temperature sensors collect temperature in real time. The sensors are connected to the data collection device, and the collection frequency and data transmission mode are set to obtain the signals output by the sensors in real time and accurately, providing comprehensive and accurate data for state recognition and flow analysis.

[0061] Specifically, during the oil displacement process, carbon dioxide enters the crude oil and dissolves in the crude oil, and its state changes accordingly. At this time, the flow data collected by the sensor cannot reflect the flow of carbon dioxide. In this embodiment, the real-time state of carbon dioxide during the oil displacement process is recognized. The state of carbon dioxide (gaseous, liquid, gas-liquid miscible, supercritical miscible) is related to factors such as temperature and pressure. By using the collected temperature and pressure data, combined with the phase equation of carbon dioxide, relevant physical parameters such as density and fugacity can be calculated. According to the corresponding relationship between these parameters and different states, the real-time state of carbon dioxide can be determined. At the same time, combined with the machine learning algorithm, by learning a large amount of known state data, a state recognition model is established to accurately determine the real-time state of carbon dioxide, accurately grasp the real-time state of carbon dioxide, and provide a key basis for subsequent flow analysis, which helps to optimize the oil displacement process and improve the oil displacement efficiency.

[0062] Specifically, according to the identified state of carbon dioxide, the carbon dioxide flow is analyzed, the physical properties of carbon dioxide in different states are different, which will affect the accuracy of flow measurement, according to the real-time state, the corresponding flow correction model is called, combined with the collected flow data and other related parameters (such as temperature, pressure, etc.), the initial flow detection result is corrected, so as to obtain more accurate real-time flow of carbon dioxide, improve the accuracy of flow monitoring, realize real-time monitoring of carbon dioxide flow in the oil displacement process, provide reliable data support for the operating personnel, so as to adjust the oil displacement parameters in time, and guarantee the efficient and stable operation of the oil displacement process.

[0063] The application is based on the data collected by the sensors at multiple positions of the carbon dioxide oil displacement system, the real-time state of carbon dioxide is identified, and the flow monitoring result is corrected, so as to accurately judge the real-time state of carbon dioxide; the initial flow detection result is corrected according to the state of carbon dioxide, so as to obtain more accurate real-time flow of carbon dioxide, improve the accuracy of flow monitoring, realize real-time monitoring of carbon dioxide flow in the oil displacement process, provide reliable data support for the operating personnel, so as to adjust the oil displacement parameters in time, and guarantee the efficient and stable operation of the oil displacement process.

[0064] Further, as Figure 2 , the acquisition data of the plurality of sensors according to the preset flow detection point position comprises:

[0065] S201, respectively setting flow sensors, temperature sensors and pressure sensors at the injection inlet, branch point, outlet of the carbon dioxide injection pipeline and different levels of the oil reservoir, and obtaining the acquisition data of each sensor at a preset time interval.

[0066] In this embodiment, in the carbon dioxide oil displacement system, sensors are arranged at the injection inlet, branch point, outlet and different levels of the oil reservoir, and the flow, temperature and pressure data at these positions can reflect the flow state and energy change of carbon dioxide in the whole oil displacement process. The parameters at the injection inlet can reflect the initial conditions of injection; the data at the branch point can reflect the distribution of carbon dioxide in different branch pipelines; the data at the outlet can reflect the oil displacement effect and overall material balance; and the parameters at different levels of the oil reservoir can reflect the sweep range and penetration of carbon dioxide in the oil reservoir.

[0067] Specifically, appropriate sensors are selected according to the working conditions (such as pipeline size, pressure range, temperature range, etc.) and measurement requirements (such as accuracy, response time, etc.) of each position. For example, ultrasonic flow meters can be selected at the injection inlet and branch point of large pipe diameter; for positions with high pressure, pressure sensors with good pressure resistance should be selected.

[0068] In the sensor data collection process, according to the dynamic changes of the oil displacement process and the monitoring requirements, appropriate collection time intervals are set. For processes that change rapidly, a shorter collection time interval (such as once per second) can be set. For relatively stable processes, the collection time interval can be appropriately extended (such as once per minute). By setting sensors at the injection inlet, branch points, outlet, and different levels of the reservoir, the flow rate, temperature, and pressure information of carbon dioxide during the entire oil displacement process can be comprehensively obtained, providing rich data support for in-depth understanding of the dynamic changes of the oil displacement process.

[0069] Further, the carbon dioxide state in the carbon dioxide monitoring process is identified according to the collected data to obtain the real-time state of the carbon dioxide, including:

[0070] S301, the carbon dioxide state characteristics are calculated according to the temperature data and pressure data in the collected data;

[0071] S302, the carbon dioxide state characteristics are input into a preset phase state recognition model to identify the carbon dioxide state in the carbon dioxide monitoring process to obtain the carbon dioxide state, wherein the carbon dioxide state includes gaseous state, liquid state, gas-liquid mixed phase state, and supercritical mixed phase state;

[0072] S303, the carbon dioxide state curve is drawn according to the carbon dioxide state to obtain the real-time state of the carbon dioxide.

[0073] In this embodiment, the state of carbon dioxide is closely related to the temperature and pressure it is in. Different temperatures and pressures will cause carbon dioxide to exhibit different phase states. Through the collected temperature and pressure data, the characteristic parameters reflecting the state of carbon dioxide can be calculated according to the phase state equation of carbon dioxide. These parameters can more accurately describe the current state of carbon dioxide. By calculating the state characteristics, the temperature and pressure data are converted into more representative parameters, which can more accurately reflect the actual state of carbon dioxide and provide a more reliable basis for subsequent phase state recognition.

[0074] Specifically, the state of carbon dioxide is identified according to the state characteristics combined with machine learning. Based on a large amount of experimental data and theoretical analysis, the neural network model is trained to obtain a preset phase state recognition model. It learns the mapping relationship between the state characteristics of carbon dioxide (such as density, fugacity, and compression factor) and different phase states (gaseous state, liquid state, gas-liquid mixed phase state, and supercritical mixed phase state). When the calculated state characteristics of carbon dioxide are input into the model, the model will judge and classify the phase state of carbon dioxide according to the learned mapping rules. The phase state recognition model can quickly and accurately identify the phase state of carbon dioxide, avoiding the subjectivity and uncertainty of manual judgment and improving the recognition efficiency and accuracy.

[0075] According to the identified carbon dioxide state, a carbon dioxide state curve is drawn with time as the horizontal axis and the carbon dioxide phase state as the vertical axis, which can intuitively show the change of the state of carbon dioxide in the oil displacement process over time. By recording and arranging the carbon dioxide phase state identified at different times and drawing in the coordinate system, the evolution process of the carbon dioxide phase state can be clearly observed, so as to obtain real-time state information of carbon dioxide. By observing the state curve, the operator can timely find abnormal changes in the carbon dioxide phase state, such as sudden phase state transition or long-term unstable state, so as to take corresponding measures for adjustment and optimization, and improve the oil displacement efficiency and safety.

[0076] Further, the carbon dioxide state characteristics calculated according to the temperature data and pressure data in the collected data include:

[0077] S401, according to the temperature data and pressure data in the collected data, the corresponding carbon dioxide state parameters are calculated by using a preset carbon dioxide phase state equation;

[0078] S402, feature extraction is performed on the carbon dioxide state parameters to obtain state characteristics related to the carbon dioxide state.

[0079] In this embodiment, the state of carbon dioxide is related to the temperature and pressure it is in. The phase state equation describes the relationship between the pressure, volume, temperature and amount of substance of a substance. By using the phase state equation, other state parameters of carbon dioxide under the given temperature and pressure can be calculated. Specifically, the Peng-Robinson (PR) equation is used for calculation.

[0080] Specifically, the collected temperature data and pressure data are preprocessed to remove obvious error data or outliers, and then the data is smoothed. The moving average method can be used to reduce the influence of data fluctuations on subsequent calculations, and at the same time, ensure the unit of data is unified. The preprocessed temperature and pressure data are substituted into the phase state equation. The PR equation is a prior art, and its principle will not be described here. The equation is solved by numerical calculation method to obtain the state parameters of carbon dioxide such as molar volume, density and compression factor. Using the phase state equation to calculate the state parameters can accurately describe the state of carbon dioxide under the current temperature and pressure based on physical principles.

[0081] The calculated carbon dioxide state parameters contain a wealth of information, but there may be some redundant or unimportant information for state identification. In this embodiment, the most representative key features of carbon dioxide state are extracted from these state parameters through feature extraction, reducing the data dimension while retaining the most important information, so as to more efficiently identify and analyze the state of carbon dioxide in the subsequent process.

[0082] Specifically, the principal component analysis method is used to calculate the covariance matrix of the carbon dioxide state parameters, and then the eigenvalues and eigenvectors are solved, the eigenvectors corresponding to the first k largest eigenvalues are selected as the principal components, and the original data is projected onto these principal components to obtain k-dimensional eigenvectors. These eigenvectors are the state characteristics related to the carbon dioxide state. By extracting representative features, the differences between different states of carbon dioxide can be better captured, and the accuracy and efficiency of state recognition can be improved.

[0083] Further, as Figure 3 , the carbon dioxide flow analysis is performed according to the real-time state of the carbon dioxide and the collected data, and the carbon dioxide monitoring management mode is adjusted to obtain the real-time flow of the carbon dioxide, which comprises:

[0084] S501, for gaseous carbon dioxide and liquid carbon dioxide, the initial flow monitoring value is corrected by the corresponding state correction matrix to obtain the corrected flow of gaseous carbon dioxide and the corrected flow of liquid carbon dioxide;

[0085] S502, for carbon dioxide in gas-liquid mixed phase state, the flow monitoring value is corrected according to the phase content of gas phase and liquid phase in gas-liquid mixed phase state to obtain the corrected flow of carbon dioxide in gas-liquid mixed phase state;

[0086] S503, for carbon dioxide in supercritical mixed phase state, the flow monitoring value is corrected according to the flow characteristics of carbon dioxide in supercritical mixed phase state to obtain the corrected flow of carbon dioxide in supercritical mixed phase state;

[0087] S504, according to the real-time state of carbon dioxide, the corrected flow of gaseous carbon dioxide, the corrected flow of liquid carbon dioxide, the corrected flow of carbon dioxide in gas-liquid mixed phase state and the corrected flow of carbon dioxide in supercritical mixed phase state are combined to obtain the real-time flow of carbon dioxide.

[0088] In this embodiment, the carbon dioxide in different states has different effects on the flow monitoring process, and the flow monitoring results collected in different states are corrected to obtain accurate real-time carbon dioxide flow.

[0089] For gaseous carbon dioxide and liquid carbon dioxide, the flow monitoring results are not much affected by the environment. According to the influence of factors such as density, viscosity, temperature and pressure of carbon dioxide in gaseous and liquid states on flow measurement, the initial flow monitoring value is corrected by the state correction matrix, which can eliminate the errors caused by these factors and obtain more accurate flow value.

[0090] For the gas-liquid mixed phase carbon dioxide, the gas phase and the liquid phase of the carbon dioxide exist at the same time, their flow characteristics and the influence on the flow measurement are different, the gas phase and the liquid phase need to be analyzed respectively, the volume or mass proportion of the gas phase or the liquid phase in the mixed fluid is reflected through calculating the phase content ratio; according to the phase content ratio, the flow monitoring value is corrected, the total flow is reasonably distributed to the gas phase and the liquid phase, and then the correction is performed respectively, so that more accurate gas-liquid mixed phase carbon dioxide flow is obtained.

[0091] For the supercritical mixed phase carbon dioxide, the traditional flow measurement method will produce a large error in the supercritical state, in the embodiment, a special correction model is established according to the flow characteristics of the supercritical mixed phase carbon dioxide, the initial flow monitoring value is corrected to obtain the accurate flow, the flow correction is performed for the unique flow characteristics of the supercritical mixed phase carbon dioxide, which can effectively solve the error problem of the traditional flow measurement method in the supercritical state, and improve the accuracy of the flow measurement in the supercritical state.

[0092] Specifically, after the carbon dioxide flow monitoring results in each state are corrected, the corrected flow in the corresponding state is combined according to the real-time recognized state of the carbon dioxide, the real-time flow of the carbon dioxide in the whole system can be obtained, and the flow of the carbon dioxide in the oil displacement process can be comprehensively and accurately reflected, thereby providing accurate data support for the control and optimization of the oil displacement process.

[0093] Further, for the gaseous carbon dioxide and the liquid carbon dioxide, the initial flow monitoring value is corrected by the corresponding state correction matrix to obtain the corrected flow of the gaseous carbon dioxide and the corrected flow of the liquid carbon dioxide, including:

[0094] S601, according to the temperature and pressure of the gaseous carbon dioxide and the liquid carbon dioxide, the gaseous flow correction coefficient and the liquid flow correction coefficient are obtained by the spline interpolation method;

[0095] S602, according to the state of the gaseous carbon dioxide and the liquid carbon dioxide, the gaseous state correction matrix and the liquid state correction matrix are constructed respectively;

[0096] S603, according to the gaseous flow correction coefficient and the gaseous state correction matrix, the initial gaseous flow monitoring value is corrected to obtain the corrected flow of the gaseous carbon dioxide;

[0097] S604, according to the liquid flow correction coefficient and the liquid state correction matrix, the initial liquid flow monitoring value is corrected to obtain the corrected flow of the liquid carbon dioxide.

[0098] In this embodiment, the physical properties (such as density, viscosity, etc.) of gaseous and liquid carbon dioxide will change under different temperature and pressure conditions, which will affect the accuracy of flow measurement. Through a large number of experiments, the data points of the flow correction coefficient under different temperature and pressure combinations can be obtained in advance. The cubic spline interpolation is used to interpolate between the known data points, so as to obtain the gaseous flow correction coefficient and the liquid flow correction coefficient corresponding to the working condition.

[0099] Specifically, according to the state of gaseous carbon dioxide and liquid carbon dioxide, the factors affecting the flow measurement of gaseous and liquid carbon dioxide are analyzed, including but not limited to pipe diameter, pipe roughness, Reynolds number of fluid, temperature change rate, pressure change rate, etc. For each influencing factor, the relationship model between each influencing factor and flow measurement error is obtained through experiment or theoretical analysis, and the corresponding correction coefficient is obtained. For example, the influence of pipe roughness can be measured by experiment to obtain the flow error under different roughness pipes, and a function relationship between roughness correction coefficient and roughness is established.

[0100] For gaseous carbon dioxide, the correction coefficients of related influencing factors are arranged in matrix form according to certain rules to obtain the gaseous state correction matrix. For liquid carbon dioxide, the correction coefficients of related influencing factors are also arranged in matrix form according to certain rules to construct the liquid state correction matrix. The gaseous and liquid state correction matrices are constructed respectively, which can correct the different characteristics of gaseous and liquid carbon dioxide, so that the correction result is more in line with the actual situation.

[0101] Specifically, the gaseous flow correction coefficient reflects the influence of the physical properties of gaseous carbon dioxide under the current temperature and pressure conditions on flow measurement, while the gaseous state correction matrix considers the influence of other factors on flow measurement. Combining the two to correct the initial gaseous flow monitoring value can comprehensively and accurately eliminate the flow measurement errors caused by various factors, and obtain the gaseous carbon dioxide flow closer to the true value. Similarly, the liquid flow correction coefficient reflects the influence of the physical properties of liquid carbon dioxide under the current temperature and pressure on flow measurement, and the liquid state correction matrix considers other influencing factors. Combining the two to correct the initial liquid flow monitoring value can accurately compensate the flow measurement deviation caused by various factors, and obtain the accurate liquid carbon dioxide flow. The specific correction formula is as follows:

[0102] ;

[0103] ;

[0104] In the formula, is the corrected flow of gaseous carbon dioxide, is the initial flow monitoring value of gaseous carbon dioxide, is a gaseous flow correction coefficient, is a gaseous state correction matrix; is a liquid carbon dioxide correction flow, is an initial flow monitoring value of the liquid carbon dioxide, is a liquid flow correction coefficient, is a liquid state correction matrix. By comprehensively considering the physical properties of the liquid carbon dioxide and other influencing factors through the state correction matrix, the initial flow monitoring value is comprehensively corrected, and the accuracy of the carbon dioxide flow measurement is improved.

[0105] Further, for the gas-liquid mixed phase carbon dioxide, according to the phase content of the gas phase and the liquid phase in the gas-liquid mixed phase, the flow monitoring value is corrected to obtain a corrected flow of the gas-liquid mixed phase carbon dioxide, including:

[0106] S701, according to the state of the gas-liquid mixed phase carbon dioxide, obtaining the phase content of the gas phase and the liquid phase in the gas-liquid mixed phase;

[0107] S702, by polynomial interpolation method, respectively calculating the flow correction coefficient of the gas phase and the liquid phase to obtain the gas phase flow correction coefficient and the liquid phase flow correction coefficient;

[0108] S703, according to the interaction of the gas-liquid two-phase in the flow process, constructing a gas-liquid mixed phase state correction matrix;

[0109] S704, according to the phase content, distributing the initial gas-liquid mixed phase flow monitoring value to the gas phase and the liquid phase to obtain the initial gas phase flow and the initial liquid phase flow;

[0110] S705, respectively calculating the initial gas phase flow and the initial liquid phase flow with the corresponding gas phase flow correction coefficient and the liquid phase flow correction coefficient to obtain the corrected gas phase flow and the corrected liquid phase flow;

[0111] S706, according to the corrected gas phase flow and the corrected liquid phase flow combined with the gas-liquid mixed phase state correction matrix, calculating to obtain the corrected flow of the gas-liquid mixed phase carbon dioxide.

[0112] In this embodiment, the phase holdup of the gas phase and the liquid phase in the gas-liquid mixed phase state is an important parameter for describing the proportional relationship between the gas phase and the liquid phase. In different gas-liquid mixed phase states (such as bubble flow, slug flow, annular flow, etc.), the distribution and proportion of the gas phase and the liquid phase are different, which will have a significant impact on flow measurement. By accurately obtaining the phase holdup, the flow of each of the gas phase and the liquid phase can be more accurately analyzed, thereby providing a basis for subsequent flow correction. By using a capacitive phase holdup sensor or a microwave phase holdup sensor, carbon dioxide in a gas-liquid mixed phase state can be measured to obtain the phase holdup of the gas phase and the phase holdup of the liquid phase. Accurate phase holdup data are a key basis for subsequent correction of the gas-liquid mixed phase flow, which helps to distinguish the flow contribution of the gas phase and the liquid phase, thereby more accurately calculating the actual flow in the gas-liquid mixed phase state.

[0113] Specifically, according to the distribution of experimental data and the interpolation accuracy requirement, a suitable polynomial order is determined, and a polynomial interpolation function of the gas phase and the liquid phase is respectively constructed in combination with the temperature and pressure data. The temperature and pressure data actually measured are substituted into the polynomial interpolation function of the gas phase and the liquid phase to respectively calculate the gas phase flow correction coefficient and the liquid phase flow correction coefficient. The polynomial interpolation method can construct a suitable polynomial function according to known data points, accurately estimate the flow correction coefficient under actual working conditions to a certain extent, and improve the accuracy of flow correction.

[0114] In the gas-liquid mixed phase flow, there are complex interactions between the gas phase and the liquid phase, such as interphase drag, interphase mass transfer, and phase distribution change. These interactions will affect the flow characteristics of the gas-liquid two phases and the accuracy of flow measurement. In this embodiment, the influence coefficients of these interactions are integrated to more accurately correct the gas-liquid mixed phase flow.

[0115] Specifically, by studying the interactions between the gas phase and the liquid phase during the flow process, the main influencing factors such as interphase drag coefficient, interphase mass transfer coefficient, and phase distribution change rate are determined, a relationship model between each interaction factor and flow measurement error is established, and the corresponding influence coefficient is obtained. For example, for the influence of interphase drag, the flow error under different interphase drag coefficients can be measured by experiment to establish a functional relationship between the drag influence coefficient and the interphase drag coefficient. The influence coefficients of various interaction factors are arranged in matrix form according to certain rules to obtain a gas-liquid mixed phase state correction matrix. The gas-liquid mixed phase state correction matrix can comprehensively consider the influence of complex interactions between the gas phase and the liquid phase on flow measurement, avoid the problem of incomplete correction caused by considering only a single factor, and improve the accuracy of flow correction.

[0116] Specifically, the initial gas-liquid mixed phase flow monitoring value is the sum of the gas-liquid two-phase flow, and the phase content reflects the proportion of the gas phase and the liquid phase in the mixed phase flow. According to the phase content, the initial gas-liquid mixed phase flow monitoring value is distributed to obtain the initial flow of the gas phase and the liquid phase, which provides a basis for subsequent flow correction of the gas phase and the liquid phase.

[0117] Specifically, the gas phase flow correction coefficient and the liquid phase flow correction coefficient respectively reflect the influence of the physical properties and flow characteristics of the gas phase and the liquid phase under the current working condition on the flow measurement. By multiplying the initial gas phase flow and the initial liquid phase flow by the corresponding flow correction coefficient, the flow measurement error caused by these factors can be compensated, and the corrected gas phase flow and the corrected liquid phase flow closer to the actual value can be obtained.

[0118] Although the corrected gas phase flow and the corrected liquid phase flow have considered the influence of the physical properties and flow characteristics of the respective phases on the flow measurement, the interaction between the gas-liquid two phases has not been fully considered. The gas-liquid mixed phase state correction matrix comprehensively considers the influence of the interaction between the gas-liquid two phases on the flow measurement during the flow process. By combining the corrected gas phase flow and the corrected liquid phase flow into a vector and performing matrix multiplication operation with the gas-liquid mixed phase state correction matrix, the flow measurement error caused by the interaction between the gas-liquid two phases can be further compensated, and a more accurate gas-liquid mixed phase state carbon dioxide corrected flow can be obtained. The calculation formula is as follows:

[0119] ;

[0120] In the formula, is the corrected gas phase flow, is the corrected liquid phase flow, is the gas-liquid mixed phase state correction matrix, is the gas phase flow in the gas-liquid mixed phase state carbon dioxide corrected flow, is the liquid phase flow in the gas-liquid mixed phase state carbon dioxide corrected flow, and the gas-liquid mixed phase state carbon dioxide corrected flow is , which comprehensively considers the influence of the physical properties, flow characteristics of the gas phase and the liquid phase, and the interaction between the gas-liquid two phases on the flow measurement, and fully corrects the gas-liquid mixed phase flow, thereby improving the accuracy of the flow measurement under the gas-liquid mixed phase state.

[0121] Further, for the supercritical mixed phase state carbon dioxide, according to the flow characteristics of the supercritical mixed phase state carbon dioxide, the flow monitoring value is corrected to obtain a supercritical mixed phase state carbon dioxide corrected flow, including:

[0122] S801, according to the relationship between the supercritical mixed phase state carbon dioxide flow and the pressure and temperature, a supercritical state flow correction coefficient is calculated;

[0123] S802, constructing a supercritical state correction matrix according to the flow characteristics of supercritical mixed-phase carbon dioxide;

[0124] S803, correcting the initial supercritical flow monitoring value according to the supercritical flow correction coefficient and the supercritical state correction matrix to obtain a supercritical mixed-phase carbon dioxide corrected flow.

[0125] In this embodiment, the physical properties (such as density, viscosity, etc.) of supercritical mixed-phase carbon dioxide are extremely sensitive to pressure and temperature, and changes in these physical properties will significantly affect the accuracy of flow measurement. In this embodiment, by establishing a relationship model between the flow of supercritical mixed-phase carbon dioxide and the pressure and temperature, the supercritical flow correction coefficient under the current pressure and temperature conditions is calculated based on the model to compensate for the flow measurement error caused by changes in pressure and temperature.

[0126] Specifically, the flow characteristics of supercritical mixed-phase carbon dioxide are relatively complex, and are influenced by factors such as pipe geometry, roughness, fluid Reynolds number, etc. in addition to pressure and temperature. For each influencing factor, a relationship model between it and the flow measurement error is established through experiments and theoretical analysis, and the corresponding correction coefficient is obtained. The correction coefficients of various influencing factors are arranged in matrix form according to certain rules to obtain a supercritical state correction matrix. The correction coefficients of various influencing factors are integrated through the matrix form, thereby more comprehensively correcting the flow of supercritical mixed-phase carbon dioxide; the supercritical state correction matrix can consider multiple factors that affect the flow measurement of supercritical mixed-phase carbon dioxide, avoiding the problem of incomplete correction caused by considering only a single factor, and improving the accuracy of flow correction.

[0127] Specifically, the supercritical flow correction coefficient mainly considers the influence of pressure and temperature on flow measurement, and the supercritical state correction matrix considers the influence of other multiple factors. Combining the two to correct the initial supercritical flow monitoring value can comprehensively and accurately eliminate flow measurement errors caused by various factors, and obtain a supercritical mixed-phase carbon dioxide flow closer to the true value. Multiply the initial supercritical flow monitoring value by the supercritical flow correction coefficient to obtain a preliminary corrected flow, and perform matrix multiplication operation on the preliminary corrected flow as a vector and the supercritical state correction matrix to obtain a supercritical mixed-phase carbon dioxide corrected flow. Combining the supercritical flow correction coefficient and the state correction matrix, the initial supercritical flow monitoring value is corrected from multiple aspects, which can effectively improve the accuracy of supercritical mixed-phase carbon dioxide flow measurement.

[0128] Further, the supercritical state flow correction coefficient is calculated according to the relationship between the supercritical mixed-phase carbon dioxide flow, pressure and temperature, comprising:

[0129] S901, according to the relationship between the supercritical mixed-phase carbon dioxide flow, pressure and temperature, combined with the Gaussian function, an interpolation model is constructed, wherein the function parameters of the Gaussian function are determined by the cross-validation method to determine the optimal value;

[0130] S902, according to the preset interpolation point combined with the interpolation model, the supercritical state flow correction coefficient is calculated.

[0131] In this embodiment, the flow of carbon dioxide in the supercritical mixed-phase state has a complex nonlinear relationship with pressure and temperature. It is often difficult to accurately describe this relationship directly through theoretical formula. In this embodiment, an interpolation model is constructed based on the combination of Gaussian function and supercritical mixed-phase carbon dioxide flow, pressure and temperature data, which is used to predict the flow correction coefficient under different pressure and temperature conditions. The formula of the Gaussian function is:

[0132] ;

[0133] In the formula, is the Gaussian function value, is the distance between the current point and the known data point, and c is the shape parameter. The optimal shape parameter value is solved by cross-validation method. The interpolation model is constructed based on the Gaussian function, and the model formula is:

[0134] ;

[0135] In the formula, is the interpolation result, T is the current state temperature, P is the current state pressure, n is the number of data points, and i≤n, is the coefficient to be solved. The Gaussian function can well fit the complex nonlinear relationship between the supercritical mixed-phase carbon dioxide flow, pressure and temperature, and improve the accuracy of the flow correction coefficient calculation. The optimal function parameters are determined by the cross-validation method, which avoids the problems of overfitting or underfitting of the model, so that the interpolation model has good prediction performance under different pressure and temperature conditions.

[0136] Based on the constructed interpolation model, the pressure and temperature combination point requiring to calculate the flow correction coefficient is taken as a preset interpolation point, the pressure and temperature values of the preset interpolation point are substituted into the interpolation model, and the corresponding supercritical state flow correction coefficient can be calculated by using the determined coefficient and Gaussian function. Different preset interpolation points can be set according to actual requirements, and the supercritical state flow correction coefficient under various pressure and temperature conditions can be flexibly calculated, so as to meet the flow correction requirements under different working conditions. The accurately calculated supercritical state flow correction coefficient provides reliable data support for the subsequent correction of the supercritical mixed phase state carbon dioxide flow monitoring value, and helps to improve the accuracy of flow measurement and the precision of process control.

[0137] Embodiment 2

[0138] In this embodiment, as Figure 4 , provide a kind of for carbon dioxide monitoring management adaptive control system for realizing the adaptive control method for carbon dioxide monitoring management described, comprising:

[0139] Data acquisition module obtains the acquisition data of multiple sensors according to the preset flow detection point position;

[0140] Carbon dioxide state identification module identifies the carbon dioxide state in the carbon dioxide monitoring process according to the acquisition data, obtains the real-time state of carbon dioxide;

[0141] Carbon dioxide flow monitoring module analyzes the carbon dioxide flow according to the real-time state of carbon dioxide combined with the acquisition data, adjusts the carbon dioxide monitoring management mode, obtains the real-time flow of carbon dioxide, to carry out adaptive control to carbon dioxide flow monitoring process.

[0142] The basic principles and main features of the present application are shown and described, and the advantages of the present application are shown and described. It should be understood by those skilled in the art that the present application is not limited by the above examples, and the above examples and descriptions in the specification are only to illustrate the principles of the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. An adaptive control method for carbon dioxide monitoring management, characterized by, The method comprises the following steps: According to the preset flow detection point position, the acquisition data of multiple sensors are obtained; According to the acquisition data, the carbon dioxide state in the carbon dioxide monitoring process is identified to obtain the real-time state of carbon dioxide, wherein the carbon dioxide state includes gaseous state, liquid state, gas-liquid mixed phase state and supercritical mixed phase state; According to the real-time state of carbon dioxide and the acquisition data, the carbon dioxide flow is analyzed, the carbon dioxide monitoring management mode is adjusted, the real-time flow of carbon dioxide is obtained, and the adaptive control of the carbon dioxide flow monitoring process is realized, wherein the carbon dioxide monitoring management mode includes correcting the flow monitoring value through the state correction matrix of gaseous state and liquid state, correcting the flow monitoring value through the phase content of gas phase and liquid phase in the gas-liquid mixed phase state, and correcting the flow monitoring value through the flow characteristics of carbon dioxide in the supercritical mixed phase state; The flow monitoring value correction through the phase content of gas phase and liquid phase in the gas-liquid mixed phase state comprises: According to the state of carbon dioxide in the gas-liquid mixed phase state, the phase content of gas phase and liquid phase in the gas-liquid mixed phase state is obtained; The flow correction coefficients of gas phase and liquid phase are calculated respectively by polynomial interpolation method to obtain the flow correction coefficients of gas phase and liquid phase; According to the interaction between gas and liquid in the flow process, a gas-liquid mixed phase correction matrix is constructed; According to the phase content, the initial gas-liquid mixed phase flow monitoring value is distributed to the gas phase and the liquid phase to obtain the initial gas phase flow and the initial liquid phase flow; The initial gas phase flow and the initial liquid phase flow are calculated respectively with the corresponding gas phase flow correction coefficient and liquid phase flow correction coefficient to obtain the corrected gas phase flow and the corrected liquid phase flow; According to the corrected gas phase flow and the corrected liquid phase flow combined with the gas-liquid mixed phase correction matrix, the corrected flow of carbon dioxide in the gas-liquid mixed phase state is calculated.

2. The adaptive control method for carbon dioxide monitoring management according to claim 1, wherein, The method comprises the following steps: Flow sensors, temperature sensors and pressure sensors are arranged at the injection inlet, branch point and outlet of the carbon dioxide injection pipeline and between different levels of the oil reservoir respectively, and the acquisition data of each sensor is obtained at a preset time interval.

3. The adaptive control method for carbon dioxide monitoring management according to claim 1, wherein, The method comprises the following steps: According to the temperature data and pressure data in the acquisition data, the carbon dioxide state characteristics are calculated; The carbon dioxide state characteristics are input into a preset phase state identification model to identify the carbon dioxide state in the carbon dioxide monitoring process and obtain the carbon dioxide state, wherein the carbon dioxide state includes gaseous state, liquid state, gas-liquid mixed phase state and supercritical mixed phase state; According to the carbon dioxide state, a carbon dioxide state curve is drawn to obtain the real-time state of carbon dioxide.

4. The adaptive control method for carbon dioxide monitoring management according to claim 3, wherein, The method comprises the following steps: According to the temperature data and pressure data in the acquisition data, the corresponding carbon dioxide state parameters are calculated by using a preset carbon dioxide phase state equation; The carbon dioxide state parameters are extracted to obtain the state characteristics related to the carbon dioxide state.

5. The adaptive control method for carbon dioxide monitoring management according to claim 3, wherein, The carbon dioxide flow analysis is performed according to the real-time state of the carbon dioxide and the collected data, and the carbon dioxide monitoring management mode is adjusted to obtain real-time carbon dioxide flow, including: For gaseous carbon dioxide and liquid carbon dioxide, the initial flow monitoring value is corrected by a corresponding state correction matrix to obtain gaseous carbon dioxide corrected flow and liquid carbon dioxide corrected flow; For carbon dioxide in a gas-liquid mixed phase state, the flow monitoring value is corrected according to the phase content of the gas phase and the liquid phase in the gas-liquid mixed phase state to obtain the corrected flow of the carbon dioxide in the gas-liquid mixed phase state; For carbon dioxide in a supercritical mixed phase state, the flow monitoring value is corrected according to the flow characteristics of the supercritical mixed phase state carbon dioxide to obtain the corrected flow of the supercritical mixed phase state carbon dioxide; The gaseous carbon dioxide corrected flow, the liquid carbon dioxide corrected flow, the corrected flow of the carbon dioxide in the gas-liquid mixed phase state, and the corrected flow of the supercritical mixed phase state carbon dioxide are combined according to the real-time state of the carbon dioxide to obtain real-time carbon dioxide flow.

6. The adaptive control method for carbon dioxide monitoring management according to claim 5, wherein, The gaseous carbon dioxide corrected flow and the liquid carbon dioxide corrected flow are obtained by correcting the initial flow monitoring value by a corresponding state correction matrix for gaseous carbon dioxide and liquid carbon dioxide, including: Gaseous flow correction coefficients and liquid flow correction coefficients are obtained by a spline interpolation method according to the temperature and pressure of gaseous carbon dioxide and liquid carbon dioxide, respectively; Gaseous state correction matrices and liquid state correction matrices are constructed according to the state of gaseous carbon dioxide and liquid carbon dioxide, respectively; The initial gaseous flow monitoring value is corrected according to the gaseous flow correction coefficient and the gaseous state correction matrix to obtain gaseous carbon dioxide corrected flow; The initial liquid flow monitoring value is corrected according to the liquid flow correction coefficient and the liquid state correction matrix to obtain liquid carbon dioxide corrected flow.

7. The adaptive control method for carbon dioxide monitoring management according to claim 5, wherein, The corrected flow of the supercritical mixed phase state carbon dioxide is obtained by correcting the flow monitoring value according to the flow characteristics of the supercritical mixed phase state carbon dioxide, including: The supercritical state flow correction coefficient is calculated according to the relationship between the supercritical mixed phase state carbon dioxide flow and the pressure and temperature; A supercritical state correction matrix is constructed according to the flow characteristics of the supercritical mixed phase state carbon dioxide; The initial supercritical state flow monitoring value is corrected according to the supercritical state flow correction coefficient and the supercritical state correction matrix to obtain the corrected flow of the supercritical mixed phase state carbon dioxide.

8. The adaptive control method for carbon dioxide monitoring management according to claim 7, wherein, The supercritical state flow correction coefficient is calculated according to the relationship between the supercritical mixed phase state carbon dioxide flow and the pressure and temperature, including: An interpolation model is constructed by combining a Gaussian function according to the relationship between the supercritical mixed phase state carbon dioxide flow and the pressure and temperature, wherein the function parameters of the Gaussian function are determined by a cross-validation method to obtain optimal values; The supercritical state flow correction coefficient is calculated according to a preset interpolation point and the interpolation model.

9. An adaptive control system for carbon dioxide monitoring management, characterized by, A self-adaptive control method for carbon dioxide monitoring management is implemented, including: The data acquisition module acquires the collection data of the plurality of sensors according to the preset flow detection point position. The carbon dioxide state recognition module recognizes the carbon dioxide state in the carbon dioxide monitoring process according to the collection data to obtain a carbon dioxide real-time state. The carbon dioxide flow monitoring module analyzes the carbon dioxide flow according to the carbon dioxide real-time state and the collection data, adjusts the carbon dioxide monitoring management mode, obtains a carbon dioxide real-time flow, and performs self-adaptive control on the carbon dioxide flow monitoring process.

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